Fact Sheet: Stratifying Quality Measures BY RACE, ETHNICITY, PREFERRED LANGUAGE, AND COUNTRY OF ORIGIN

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1 MINNESOTA STATEWIDE QUALITY REPORTING AND MEASUREMENT SYSTEM Fact Sheet: Stratifying Quality Measures BY RACE, ETHNICITY, PREFERRED LANGUAGE, AND COUNTRY OF ORIGIN Overview Minnesota s 2008 Health Reform Law requires the Commissioner of Health to establish a standardized set of quality measures for health care providers. This standardized quality measure set is known as the Minnesota Statewide Quality Reporting and Measurement System (Quality Reporting System). The Minnesota Department of Health (MDH) updates the measure set annually. MDH published its adopted rule and standardized measure set for 2016 reporting on January 11, The Quality Reporting System includes clinic and hospital quality measures that are submitted via different mechanisms from three primary data sources: Providers patient medical records, which are increasingly stored in an electronic health record (EHR) system; Patient experience of care surveys that providers dispense to patients through survey vendors; and Administrative claims, which are stored in a practice management system and are also referred to as discharge data in the hospital setting. To cover essential roles such as data collection, measurement development and maintenance, provider education, and making recommendations for changes to the measurement set, MDH contracts with a consortium of vendors that is led by Minnesota Community Measurement (MNCM) and includes Stratis Health and the Minnesota Hospital Association. Health Equity Although Minnesota ranks among the healthiest states in the nation, it simultaneously experiences significant and persistent disparities in health outcomes for some segments of the population. To eradicate these disparities, it is important for the State to foster health equity, which means creating the conditions in which all people have the opportunity to attain their highest possible level of health. 1 One of the challenges related to developing and evaluating programs to address and eliminate health disparities is the relative lack of data on many of the 1 MDH. (2014). Advancing Health Equity in Minnesota: Report to the Minnesota Legislature Saint Paul, MN: Minnesota Department of Health.

2 STRATIFYING QUALITY MEASURES contributing socio-demographic factors, including data directly available to communities that are most impacted by health disparities and inequities. 2 The need for a consistent, statewide requirement for data reporting on race, ethnicity, and language in Minnesota has been noted among the recommendations in several prior legislative reports from MDH. In its 2014 Advancing Health Equity report, MDH recommended the creation of race, ethnicity, and language data collection standards and requirements that would be implemented across all programmatic areas, and stressed that any data collection, analysis or dissemination approaches needed to be developed in close collaboration with communities that experience disparities. Quality measure stratification Socio-demographic characteristics are important for understanding system-wide variations and disparities in quality of care because evidence shows that many of the factors that most heavily impact a person s health status exist outside of the healthcare system. Reporting on quality of care in the absence of socio-demographic characteristics may actually deepen the inequities and disparities that currently exist in our health care system by creating incentives for providers to minimize or avoid treating patients from communities that experience disparities and are less likely to contribute to strong performance on existing measures of quality of care. 3 One way to combine socio-demographic factors with quality measures is to report measure results by different groups or combinations of groups also known as stratifying results. Stratification refers to calculating health care performance scores separately for different patient groups based on some characteristic. For example, groups could be constructed based on race and performance scores computed for each group. Stratification enables the identification of healthcare disparities for certain patient groups and it can unmask healthcare disparities by examining performance for groups who have been historically disadvantaged compared to groups who have not been disadvantaged. Legislative requirements Recognizing these issues, in 2014, the Minnesota Legislature directed MDH to develop an implementation plan for stratifying Quality Reporting System measures based on disability, race, ethnicity, language, and other socio-demographic factors that are correlated with health disparities and impact performance on quality measures. 4 The legislation required MDH to develop the plan in consultation with: consumer, community and advocacy organizations representing diverse communities; health plan companies; providers; quality measurement 2 MDH and DHS. (2011). Collection of Racial/Ethnic Health Data by the Minnesota Departments of Health and Human Services. Saint Paul, MN: Minnesota Departments of Health and Human Services. 3 National Quality Forum. (2014). Risk Adjustment for Socioeconomic Status or other Socio-demographic Factors. Washington DC: National Quality Forum. 4 Minnesota Laws 2014, Chapter 312, Article 23, Section 10. 2

3 STRATIFYING QUALITY MEASURES organizations; and safety net providers that primarily serve communities and patient populations with health disparities. MDH submitted this plan to the Legislature in early The Legislature then enacted requirements that MDH stratify five quality measures by race, ethnicity, preferred language, and country of origin. 6 Current data collection and reporting Clinic measures Most Minnesota clinics already capture patient race, ethnicity, preferred language, and country of origin information in their EHR systems. MNCM has been voluntarily collecting race, Hispanic ethnicity, preferred language, and country of origin information from medical groups since 2010, building on earlier voluntary efforts begun by a number of medical groups as early as MNCM issued a report in January 2015 that stratified five quality measures by these sociodemographic factors statewide and by geographic region. 8 These measures which are also in the Quality Reporting System are: Optimal Diabetes Care; Optimal Vascular Care; Optimal Asthma Care Adult; Optimal Asthma Care Child; and Colorectal Cancer Screening. Additionally, the clinic patient experience of care survey that is in the Quality Reporting System asks respondents for their age, gender, education level, race, and ethnicity. However, there is currently no public reporting on patient experience of care in Minnesota that is broken out by those factors. Hospital measures Minnesota hospitals capture patient race, ethnicity, and preferred language information to a significant extent to meet federal requirements. Because nearly all EHR-based and patient experience hospital measures in the Quality Reporting System are highly aligned with federal measurement specifications and rely on submission of the data to federal agencies, MDH has little control over the content of data submission and relies on summary data reported by federal agencies. Although key federal programs require hospitals to submit race and ethnicity information when reporting quality measures with data populated by EHRs, this data is not available publicly and it is not clear whether CMS will release patient socio-demographic information upon request. 5 MDH. (2015). Stratifying Health Care Quality Measures Using Socio-demographic Factors: Report to the Minnesota Legislature Saint Paul, MN: Minnesota Department of Health. 6 Minnesota Laws Chapter 71, Article 9, Sections 4-7, which is codified as Minnesota Statutes, section 62U.02, subdivision 1(b) (2015). 7 MNCM. (2010). Handbook on the Collection of Race/Ethnicity/Language Data in Medical Groups. Minneapolis, MN: Minnesota Community Measurement. 8 MNCM. (2015) Health Equity of Care Report: Stratification of Health Care Performance Results in Minnesota by Race, Hispanic Ethnicity, Preferred Language and Country of Origin. Minneapolis, MN: Minnesota Community Measurement. 3

4 FACT SHEE T TITLE Provider organizations and health plans use administrative claims data to calculate quality measures, and some of these hospital measures are in the Quality Reporting System. These measures are developed and maintained by national and federal organizations, and they do not require the inclusion of race, ethnicity, preferred language, and country of origin in their calculation. Implementing Stratification Requirements Reporting requirements To meet the legislative requirements to stratify five quality measures by race, ethnicity, preferred language, and country of origin and given the schedule of existing data collection through MNCM, MDH is requiring clinics to report these socio-demographic factors beginning in July 2017 for the Optimal Asthma Control Adult, Optimal Asthma Control Child, and Colorectal Cancer Screening quality measures for July 1, 2016 through June 30, 2017 dates of service, and the Optimal Diabetes Care and Optimal Vascular Care quality measures beginning in January 2018 for January 1, 2017 through December 31, 2017 dates of service. For initial stratification, MDH is not including hospital measures. While many hospitals capture these data elements within their electronic health records, the federal programs that have developed most of the hospital measures that are used in the Quality Reporting System do not publicly report these data elements in their measures. MDH will continue to monitor trends at local and national levels, and will seek comments on stratifying hospital measures in future years. Stratification principles The Department s approach to stratification is based on the following principles, which seek to balance legislative timeline expectations, provider burden, and feasibility: Build on existing voluntary submission of race, ethnicity, preferred language and country of origin data that is led by MNCM. To minimize provider burden, the variable specification for data submission on race, ethnicity, preferred language, and country of origin will be those that are already being used for voluntary submission, so that providers do not need to make changes to existing data collection processes. MDH will not publish stratified data at the clinic level, but rather at the statewide, county, and zip code levels as data quality permits. MDH is staging the implementation of data submission requirements so as to give providers who are not already submitting this information to MNCM time to prepare for required 4

5 FACT SHEE T TITLE submission. Providers that are not ready to submit these data elements can submit a request for variance to MDH 9. MDH is not requiring providers to share any patient-level data on these factors with the Department. Public comments During the public comment period on the proposed 2016 Quality Rule, MDH invited comment on the implementation of legislative requirements, and specifically sought input on the following questions: 1. Currently, MNCM is reporting race, Hispanic ethnicity, preferred language, and country of origin data on a statewide and regional basis for Optimal Asthma Control Adult; Optimal Asthma Control Child; Colorectal Cancer Screening; Optimal Diabetes Care; and Optimal Vascular Care. Are these the five measures that should be prioritized for stratification now, or are there other physician clinic measures that should be prioritized? 2. Recognizing that data submission within a given calendar year involves dates of service from the previous year, when should required reporting of race, ethnicity, preferred language, and country of origin begin 2017 or 2018? 3. What physician clinic measures should be prioritized for stratification in the future? 4. Which socio-demographic factors and sources of this data should the Department consider when developing its plans for broader stratification in 2018? 5. What support (e.g., education, technical assistance) do providers need to be able to capture and report this socio-demographic data? MDH received 13 comments related to stratification, representing 61 organizations and five individuals. All of the comments were supportive of adding race, ethnicity, preferred language, and country of origin reporting requirements to the Quality Rule. Commenters shared their perspectives on when the mandate should take effect, which measures should be stratified in the future, and which additional socio-demographic factors should be used in stratification. Minnesota Department of Health Health Economics Program PO Box St. Paul, MN health reform@state.mn.us January 11, 2016 To obtain this information in a different format, call: Printed on recycled paper. 9 Minnesota Rule provides discretionary authority for the Commissioner of Health to grant variances to a data submitter for a reported quality measure collection or submission specification if the data submitter demonstrates good cause. 5

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